Gradient-based Adaptive Importance Samplers

Deep Convolutional Transform Learning

PENDANTSS: PEnalized Norm-ratios Disentangling Additive Noise, Trend and Sparse Spikes

Deep Probabilistic Matrix Factorization on Graphs: Application to Drug Repositioning in Antimicrobial Resistance

Multi-label Deep Convolutional Transform Learning for Non-intrusive Load Monitoring

ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis

Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting

Semi-supervised Deep Convolutional Transform Learning for Hyperspectral Image Classification

Deep Probabilistic Matrix Factorization on Graphs: Application to Drug Repositioning for Monkeypox

Deeply Transformed Subspace Clustering

Graphem: EM Algorithm for Blind Kalman Filtering Under Graphical Sparsity Constraints

A divergence-based condition to ensure quantile improvement in black-box global optimization

DeConFuse: a deep convolutional transform-based unsupervised fusion framework

A dynamical model for stock forecasting via deep recurrent dictionary learning

DeConDFFuse : Predicting Drug-Drug Interaction using joint Deep Convolutional Transform Learning and Decision Forest fusion framework

Deep Latent Factor Model for Predicting Drug Target Interactions

Deep Convolutional K-Means Clustering

A new non-convex framework to improve asymptotical knowledge on generic stochastic gradient descent

A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials

Primal-dual interior point optimization for penalized least squares estimation of abundance maps in hyperspectral imaging

Algorithme primal-dual de points intérieurs pour l'estimation pénalisée des cartes d'abondances en imagerie hyperspectrale

Simulated annealing: a review and a new scheme

Proximal-based adaptive simulated annealing for global optimization

A Divergence-Based Condition to Ensure Quantile Improvement in Black-Box Global Optimization

GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models

Regularized Rényi divergence minimization through Bregman proximal gradient algorithms

Langevin-based Strategy for Efficient Proposal Adaptation in Population Monte Carlo

Adaptive simulated annealing through alternating Renyi divergence minimization

Adaptive importance sampling for heavy-tailed distributions via α-divergence minimization

Fight the Pandemic: Highlights From the 2020 IEEE 5-Minute Video Clip Contest

Démélange, déconvolution et débruitage conjoints d’un modèle convolutif parcimonieux avec dérive instrumentale, par pénalisation de rapports de normes ou quasi-normes lissées (PENDANTSS)

On variational inference and maximum likelihood estimation with the $ \lambda $-exponential family

DeConFuse: A Deep Convolutional Transform based Unsupervised Fusion Framework

DeConFCluster: Deep Convolutional Transform Learning based Multiview Clustering Fusion Framework

DeConDFFuse: Predicting drug-drug interaction using joint deep convolutional transform learning and decision forest fusion framework

Majorize-minimize linesearch for inversion methods involving barrier function optimization

Block delayed Majorize-Minimize subspace algorithm for large scale image restoration

Sparse Graphical Linear Dynamical Systems

Graphical Inference in Linear-Gaussian State-Space Models

PALMA, an improved algorithm for DOSY signal processing

Efficiency of linesearch strategies in interior point methods for linearly constrained signal restoration

Primal-dual Interior-Point Optimization Based on Majorization-Minimization for Edge-Preserving Spectral Unmixing

SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems

Lightweight U-Net for Lesion Segmentation in Ultrasound Images

An instrumental and computational pipeline for visualizing free viral particles

Gradient-based adaptive importance samplers

A stochastic use of the Kurdyka-Lojasiewicz property: Investigation of optimization algorithms behaviours in a non-convex differentiable framework

Probabilistic modeling and inference for sequential space-varying blur identification

A probabilistic incremental proximal gradient method

Particle Filtering for Online Space-Varying Blur Identification